New Methods for the Cross-Section of Returns

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New Methods for the Cross-Section of Returns
G. Andrew Karolyi
Cornell University SC Johnson College of Business
Stijn Van Nieuwerburgh
Columbia University Graduate School of Business
The Review of Financial Studies / v 33 n 5 2020

The cross-section and time series of stock returns contains a wealth of information
about the stochastic discount factor (SDF), the object that links cash flows to prices.
A large empirical literature has uncovered many candidate factors—many more than
seem plausible—to summarize the SDF. This special volume of the Review of Financial
Studies presents recent advances in extracting information from both the cross-section
and the time series, in dealing with issues of replication and false discoveries, and
in applying innovative machine-learning techniques to identify the most relevant asset
pricing factors. Our editorial summarizes what we learn and offers a few suggestions
to guide future work in this exciting new era of big data and empirical asset pricing. hhaa019.pdf (160.38 KB, 需要: 1 个论坛币)

2020-4-25 16:16:25 上传

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这个PDF只是简介性的，没有那几篇论文